1. Field of the Invention
This invention relates generally to a system and method for enhancing vehicle diagnostic and prognostic algorithms and, more particularly, to a system and method for enhancing vehicle diagnostic and prognostic algorithms and vehicle maintenance practices by fusing vehicle information from multiple sources.
2. Discussion of the Related Art
Diagnostics monitoring of various vehicle systems is an important vehicle design consideration so as to be able to quickly detect system faults, and isolate the faults for maintenance and service purposes. These vehicle systems typically employ various sub-systems, actuators and sensors, such as yaw rate sensors, lateral acceleration sensors, steering hand-wheel angle sensors, etc., that are used to help provide control of the vehicle. If any of the sensors, actuators and sub-systems associated with these systems fail, it is desirable to quickly detect the fault and activate fail-safe (fail-silent or fail-operational) strategies so as to prevent the system from improperly responding to a perceived, but false condition. It is also desirable to isolate the defective sensor, actuator or sub-system for maintenance, service and replacement purposes. Thus, it is necessary to monitor the various sensors, actuators and sub-systems employed in these systems to identify a failure.
It is a design challenge to identify the root cause of a fault and isolate the fault all the way down to the component level, or even the sub-system level, in a vehicle system. The various sub-systems and components in a vehicle system, such as vehicle brake system or a vehicle steering system, are typically not designed by the vehicle manufacturer, but are provided by an outside source. Because of this, these components and sub-systems may not have knowledge of what other sub-systems or components are doing in the overall vehicle system, but will only know how their particular sub-system or component is operating. Thus, these outside sub-systems or components may know that they are not operating properly, but will not know if their component or sub-system is faulty or another sub-system or component is faulty. For example, a vehicle may be pulling in one direction, which may be the result of a brake problem or a steering problem. However, because the brake system and the steering system do not know whether the other is operating properly, the overall vehicle system may not be able to identify the root cause of that problem.
Each individual sub-system or component may issue a diagnostic trouble code indicating a problem when they are not operating properly, but this trouble code may not be a result of a problem with the sub-system or component issuing the code. In other words, the diagnostic code may be set because the sub-system or component is not operating properly, but that operation may be the result of another sub-system or component not operating properly. It is desirable to know how reliable the diagnostics codes are from a particular sub-system or component to determine whether that sub-system or component is the fault of a problem.
Diagnostic and Prognostic techniques for vehicle state of health monitoring can help forecast the occurrence of a problem in order to take preventive measures before significant damage is done. These techniques become more important for systems where the failure of the system can have critical implications. Further, system manufacturers can help prevent their customers from being dissatisfied due to the failure of various systems by using diagnostic and prognostic techniques.
Efforts have been made in the past to develop diagnostic and prognostic techniques to detect and localize performance degradations in various operating systems. One existing method based on the principles of diagnosis and prognosis uses temporal data mining.